Top Data & Analytics Jobs in Pittsburgh, PA

Designs, builds, and supports scalable data warehouse solutions, including pipelines, data models, transformations, governance, metadata, and documentation. Leads data requirements analysis, migration and modernization efforts, source-to-target mapping, DDL and SCD modeling, troubleshooting, and root-cause analysis. Collaborates with engineering, business analysis, quality engineering, and reporting teams to deliver maintainable data solutions across Oracle and Hadoop platforms.

Leads data analysis and advanced analytics workstreams for clients, using statistical modeling, machine learning, data visualization, and Adobe Experience Cloud technologies to improve operations and strategic decision-making. Manages project planning, budgeting, execution, and completion while mentoring teams, maintaining data integrity and security, building Tableau and Power BI dashboards, identifying business opportunities, and integrating innovative analytics practices.

Design and architect scalable healthcare data systems, core data models, and production data pipelines. Integrate and normalize healthcare data using TUVA, OMOP, and FHIR standards; establish data quality and governance; optimize performance; deploy secure cloud infrastructure; ensure regulatory compliance; and build bi-directional EMR integrations. The role also requires independent technical decision-making, test automation, CI/CD, and DevOps practices in a fast-paced healthcare technology startup.

Builds and architects complex ETL pipelines and data integrations for an enterprise data lakehouse. Responsibilities include designing workflows, monitoring data movement across cloud and on-premise systems, improving data quality, implementing master data management, documenting lineage, troubleshooting integrations, and standardizing data processes. The role collaborates with business units, analysts, visualization engineers, IT, and data scientists to enable new data sources and resolve complex technical issues.

Leads the enterprise Flexera Data Platform and IT asset management lifecycle for hardware and software. Responsibilities include platform management, discovery and normalization, data governance, reporting, compliance, CMDB maintenance, software lifecycle management, automation, and AI-enabled analytics. The role analyzes complex datasets, resolves data quality issues, coordinates RFCs and upgrades, supports audit readiness, manages stakeholder requests, and drives process improvements across cross-functional technology and sourcing teams.

Leads enterprise data architecture, SQL Server administration, data warehouse design, ETL/ELT pipelines, Azure data platforms, data governance, master data management, and business intelligence strategy. Partners with business and IT stakeholders to deliver scalable analytics solutions across financial, HR, CRM, operational, and practice management systems. Provides technical leadership, vendor coordination, architecture documentation, and mentorship.

Designs and maintains CORE’s enterprise analytics data platform, including dimensional data warehouses, ETL/ELT pipelines, semantic models, and governed datasets. Integrates clinical, financial, workforce, donor, and operational data while ensuring platform security, reliability, performance, quality, lineage, documentation, and monitoring. Supports Power BI, advanced analytics, and responsible AI initiatives, collaborates with technical and business stakeholders, and translates requirements into sustainable production solutions.

Owns the enterprise Data Lakehouse platform, including operations, configuration, integrations, monitoring, validation, issue resolution, vendor management, releases, documentation, security controls, and lifecycle planning. Translates business and data requirements into platform solutions, coordinates cross-functional technology teams, and ensures reliable support for business intelligence, reporting, analytics, and AI use cases. Provides technical leadership and guidance without direct personnel-management responsibility.

Builds and maintains scalable data pipelines and reusable datasets in Databricks. Ingests, validates, transforms, and models structured and unstructured data using Python, PySpark, and SQL. Integrates warehouse and cloud analytics systems, supports Tableau and Spotfire reporting, improves reliability and performance, and implements testing, monitoring, documentation, and CI/CD. Collaborates with technical and business stakeholders while providing technical guidance, code reviews, and mentorship.

Leads the architecture, development, and production rollout of an enterprise batch feature store. Designs and tunes PySpark and Impala SQL pipelines using Hive and Oracle, establishes data quality and monitoring standards, manages batch scheduling, and guides developers through technical reviews, releases, and troubleshooting. Coordinates stakeholders, mentors engineers, supports Agile delivery, and ensures CI/CD, testing, change management, and SDLC compliance.